An Effective Stochastic Approach for Optimal Energy Resource Management in Hybrid AC–DC Microgrids

This paper develops a new management framework for optimal operation of the hybrid AC–DC microgrids incorporating renewable energy sources and storages. Hybrid microgrid consists of two parts of AC and DC to supply the AC and DC loads, respectively. The power exchange capability of hybrid microgrids between the AC and DC parts makes it possible to reduce the total microgrid costs, effectively. To make it a realistic analysis, a stochastic method based on cloud theory is proposed to model the uncertainty effects of wind turbine power, photovoltaic power, load demand and market price sufficiently. The proposed framework makes use of a new optimization algorithm based on flower pollination mechanism to minimize the total network costs through the optimal dispatch of the units. Also, a three-stage modification method is proposed to improve the population diversity and avoid the premature convergence. The performance of the proposed method is examined on the IEEE test system through two different operation scenarios.